Apples and Oranges

Aside from the books being studied, it seems that quantitative methods and literary studies have little in common. The former utilize a narrow approach, specified data, and techniques independent of the books themselves (ie. math); the later relies on conjecture. Comparing the two feels like looking at apples and oranges–while both are fruits, their particular distinctions greatly overshadow their limited similarities.   

Ultimately though, it does seem poignant to remember the close dependence of both quantitative methods and literary studies on variables like time, environment, technology, ect. This shared history critically shapes the circumstances of both approaches, however, the efforts of each in reaction are highly different. Quantitative methods, whether empirical or derived, function under the direct presence (and often absence) of data. As Weedon and Eliot both recognize, these data sets available are often insufficient. Time and loss challenge the data of book history, and as such quantitative methods have turned to narrower data sets and studies that can be more assuredly relied on. It is this ‘material’ world (coined by Eliot), though riddled with its own scope of inconsistencies in fact, from which a more accurate understanding of book history can be made. While such a rationalized perspective is probably best attributed to the passage of time Weedon/Eliot have, I found their more realistic favorable to the broad, and overreaching claims of Febre, Martin, and Darnton. Unlike quantitative methods, in the face of historical variables, literary studied have turned to guess.    

It’s as Eliot says, “I needed to see the forest, not a host of additional trees” (285). After the passage of time, the destruction of texts/records, and the basic uncertainty of history, it is seemingly impossible to ‘recreate this forest’. Although both quantitative methods and literary studies rightfully recognize the interdisciplinary nature of this forest, the trees have been cleared for both. It is only quantitative methods of book history though, that have looked to supplement this absence. Quantitative methods focus on actual data available, and although this pool is ever-changing (technology, discoveries, ect.), it has always been more consistent than the claims made in literary studies like Sociology of Text, Annales School, or Communication Circuit. These literary studies rely on uncertainties–authorial intent, context of place and person, culture. Although arguably more entertaining and flashy than quantitative methods (even Eliot and Miller admit the oft boring practice of collecting and analyzing data), literary study will never have the same verified credibility that the more recent field of quantitative methods allot to the ‘history of the book’. I’m curious to see how the two approaches to the history of books interact throughout the rest of this course (if at all).

Finally, as an aside, I am curious how quantitative methods manipulate data to the interests of their studies. Eliot remarks that data sets are categorized, simplified, and ordered (291). Weedon similarly offers many quantitative methods, each of which can be applied to a specific scenario and data set. These techniques reminded me of the practices of the bestseller lists we first looked at. In both, the data seems manipulated for some purpose. I’m curious if quantitative methods have applied this manipulation out of necessity, or intent? To me, this paradox seems to lean toward necessity, but I am curious to see what others think. 

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3 thoughts on “Apples and Oranges

  1. I find that I am leaning towards agreeing with one of your last statements — that book historians do indeed manipulate data at times and for reasons most often determined by necessity rather than intent. As Weedon addressed, some of the limits of data include its quality (oftentimes incomplete or unreliable) as well as the overall quantity of data (data pools that are too small may not help to establish completely realistic interpretations whereas data pools that are too large may make it impossible to draw any conclusions whatsoever.) In my opinion, there is a certain extent by which historians may interpret data in order to serve the purposes of their research that is forgivable, but it also adds to my hesitancy to put too much stake in the findings of book historians.

  2. I would have to agree with the statements about quantitative methods manipulating data to the interests of their studies. With my general understanding of mathematics, I am curious as well, to see how these things tie together to display a particular view of book history. Is there a limit or range on how much you can construct/alter data to show what you what you want to be seen? I also can’t wait to have a better understanding of the concepts so I can fully and more accurately interpret the graphs and data. I realize now that it is important to be “educated” in book history when dealing with actual data and examples of book history. Excellent points here.

  3. In response to Jeff’s post, I might question the characterization of McKenzie’s sociology of the text, the Annales school of historians, and Darnton’s communications circuit as literary approaches based on “conjecture” or “guess.” All of these approaches–different as they may be–fall under the rubric of “history of the book.” Which is why we read them.

    As we read more works in this field, we’ll want to be careful not to confuse presentation with methodology. For example, Darnton’s discussion of the book circuit in 18th-century France may obscure his study of publishers’ and printers’ and booksellers’ records, in a quantitative way. He presents us with the story, rather than the numbers–a rhetorical choice, and one that may not persuade everybody.

    If, as Ira and Brie suggest, book historians cherry pick or manipulate their data, it seems unlikely to me that they do so any more than other historians trying to reconstruct a picture of the past for those living today. Even social scientists today, with reasonable survey methodology and good sampling techniques, don’t always accurately capture the big picture and, certainly, can’t capture any individual’s lived experience. Both book history and social science rely on qualitative methods (such as ethnography or content analysis) for that.

    Quantitative data provides another perspective on the context of literary works and literary culture that study of individual classic works of literature and author biographies simply cannot provide, so it seems reasonable to appreciate it for what it can offer us and do our very best to analyze and interpret that data in an unbiased way, while recognizing–and accounting for–the limitations of the approach.

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